Here we propose to develop a new approach for genomic analysis of gene expression level changes. Changes in the expression pattern of a group of genes are believed to profile the physiological functions of those genes, and can illustrate the molecular characteristic of a complex disease such as breast cancer at various stages. Therefore, efficient measurements of gene expression level using an accurate, rapid and cost-effective way as proposed here will allow for the understanding of the breast cancer development and for the diagnosis of the disease. The proposed approach utilizes two methods, the solid phase capturable single base extension (SPC-SBE) method and the real competitive PCR (rcPCR) approach. SPC-SBE is a multiplex genotyping method developed by the PI that employs matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and a molecular affinity system. The SPC-SBE method includes a procedure for the specific isolation of DNA extension fragments prior to the MS measurement, allowing higher throughput and accuracy in multiplex genotyping of genetic variations. Since SPC-SBE offers a robust genotyping of heterozygous SNPs with higher level of accuracy and throughput, we hypothesize the method can be a robust approach for gene expression analysis, when adapting the rcPCR approach. The specific aims of the proposed research include: (1) Analysis of the expression level of 50 genes using SPC- SBE and rcPCR. We will first develop an expression analysis tool using SPC-SBE and rcPCR. We will use a well studied system, gene expression changes during retinal development, as a model to establish the proposed method. (2) Optimization of the sample preparation process for MALDI-TOF MS. We will enhance the accuracy of the quantitative genotyping (and thus the gene expression level measurement) by optimizing the sample crystal preparation and data analysis. (3) Verification of the proposed system for breast cancer samples. We will demonstrate our system for monitoring gene expression changes in breast cancer. The result will be compared with previous studies. The proposed method will permit high throughput, accurate and cost-effective monitoring of gene expression level changes in breast cancer. Therefore, the method will provide easy classification of breast cancer subtypes and accurate determination of progression stages, which is critical for individual patient assessment and for personalized treatment. [unreadable] [unreadable] [unreadable]